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This paper examines the stationary dimethyl ether (DME) oxidation behavior of state-of-the-art diesel oxidation catalysts (DOCs) under both model conditions and scenarios that closely resemble real-world application. The study investigates the implications of new hydrocarbon (HC) mixtures present in the exhaust gas matrix of DME-fueled combustion engines, focusing on the potential application of series-production DOCs within exhaust aftertreatment systems. Utilizing a synthetic gas test bench (SGB), gas mixtures are designed to simulate realistic operating conditions, including one scenario with 100% DME fuel and another where DME is blended with Diesel fuel, leading to varying HC mixtures. Experimental findings reveal that 2 out of 5 DOCs convert <50% of the raw DME emissions reaching temperatures of 374 °C. Under these realistic conditions, also 0 out 5 DOCs convert <80% until reaching 379 °C. Notably, while DME partly inhibits NO oxidation at intermediate temperatures, it does not promote N2O formation as propene does. The experiments further reveal distinct temperature-dependent patterns of secondary emissions, including formaldehyde, formic acid, carbon monoxide, methanol, and methyl formate. These secondary emissions are strongly affected by the exhaust gas composition and are substantially reduced or shifted under conditions representative of DME-containing engine exhaust.

This article presents data collected during a measurement campaign conducted on a synthetic gas test bench (SGB) at the Chair of Thermodynamics of Mobile Energy Conversion Systems (TME). The campaign includes 23 light-off experiments utilizing five state-of-the-art diesel oxidation catalysts (DOCs) with varying platinum and palladium formulations. The primary objective is to investigate the oxidation behavior of dimethyl ether (DME) and its impact on other reactions within exhaust gas aftertreatment. Five distinct gas compositions were employed to replicate reduced, model, and realistic conditions for simulating DME and DME/diesel fuel blend exhaust gases. The dataset comprises comprehensive test bench data, including temperature readings, mass flow controller metrics, and gas analytical values. These data are curated primarily for analyzing the light-off temperature ramp, while also encompassing the time frame from pre-conditioning to post-conditioning. This dataset offers valuable insights into DME's oxidation behavior, its co-oxidation effects, and the formation of secondary emissions. The dataset includes results from 20 experiments across DOCs 1-5 for four different gas matrices: 1. A reduced gas matrix for pure DME oxidation with only O2. 2. A realistic gas matrix for DME oxidation under actual exhaust gas conditions, incorporating CO, NO, and CO2 into the reduced mix to simulate DME combustion exhaust. 3. A reduced gas mix for pure DME and propene co-oxidation with only O2. 4. A realistic gas matrix for DME and propene co-oxidation under genuine exhaust conditions, again integrating CO, NO, and CO2 to simulate a DME/diesel exhaust scenario. Additionally, three experiments involving DOCs 1, 3, and 5 are included with gas mixture 5: 5. This realistic gas mix excludes any hydrocarbons (HC) to assess their influence on NO oxidation. The datasets follow this nomenclature: DOC_X_GM_Y, where: X indicates the respective DOC number (1-5), Y denotes the corresponding gas matrix (GM), ranging from 1 to 5. The datasets for exhaust gas analytics encompass key components such as DME, O2, CO, CO2, NO, along with additional HC species generated during the oxidation process of DME and propene. Notably prominent components include formaldehyde, formic acid, methanol, and nitric oxide; N2 is used as a carrier.

This article presents data collected during a measurement campaign conducted on a synthetic gas test bench (SGB) at the Chair of Thermodynamics of Mobile Energy Conversion Systems (TME). The campaign includes 23 light-off experiments utilizing five state-of-the-art diesel oxidation catalysts (DOCs) with varying platinum and palladium formulations. The primary objective is to investigate the oxidation behavior of dimethyl ether (DME) and its impact on other reactions within exhaust gas aftertreatment. Five distinct gas compositions were employed to replicate reduced, model, and realistic conditions for simulating DME and DME/diesel fuel blend exhaust gases. The dataset comprises comprehensive test bench data, including temperature readings, mass flow controller metrics, and gas analytical values. These data are curated primarily for analyzing the light-off temperature ramp, while also encompassing the time frame from pre-conditioning to post-conditioning. This dataset offers valuable insights into DME's oxidation behavior, its co-oxidation effects, and the formation of secondary emissions. The dataset includes results from 20 experiments across DOCs 1-5 for four different gas matrices: 1. A reduced gas matrix for pure DME oxidation with only O2. 2. A realistic gas matrix for DME oxidation under actual exhaust gas conditions, incorporating CO, NO, and CO2 into the reduced mix to simulate DME combustion exhaust. 3. A reduced gas mix for pure DME and propene co-oxidation with only O2. 4. A realistic gas matrix for DME and propene co-oxidation under genuine exhaust conditions, again integrating CO, NO, and CO2 to simulate a DME/diesel exhaust scenario. Additionally, three experiments involving DOCs 1, 3, and 5 are included with gas mixture 5: 5. This realistic gas mix excludes any hydrocarbons (HC) to assess their influence on NO oxidation. The datasets follow this nomenclature: DOC_X_GM_Y, where: X indicates the respective DOC number (1-5), Y denotes the corresponding gas matrix (GM), ranging from 1 to 5. The datasets for exhaust gas analytics encompass key components such as DME, O2, CO, CO2, NO, along with additional HC species generated during the oxidation process of DME and propene. Notably prominent components include formaldehyde, formic acid, methanol, and nitric oxide; N2 is used as a carrier.

Digital innovations often follow a more fluid innovation process and, therefore, require different ways of managing the front end of innovation. Agile as alternative to established front end management practices is often suggested, potentially combined with Stage‐Gate, in what is called a hybrid Agile‐Stage‐Gate model, to reap the benefits from both. Implementing the hybrid model in the front end is however not sufficient for firms with separate Research and Development departments to succeed. In such organizations digital innovations still need to be transferred from Research, where the front end work on digital innovations takes place, to the Development department, where formal development actually starts. Yet, such front end transfers have been described as inefficient and ineffective. Realizing digital innovation front end transfers is likely even more challenging because of their fluid definition. In the absence of extant theory on front end transfers in such a setting, this research uses a case study approach to analyze the front end transfer experiences of the Research department of a firm in the lighting industry that is undergoing a transformation from traditional to digital lighting. The in‐depth analysis of triangulated data on eight front end projects shows that Research struggles to transfer digital innovations to Development, because transfer practices in terms of management, scope, and synchronization, turn out to be inherently challenging in a hybrid Agile‐Stage‐Gate setting. Specifically, the results reveal that each transfer practice plays an intricate role in either facilitating (i.e., transfer management) or inhibiting (i.e., transfer scope and synchronization) front end transfers of digital innovations. The discovery of these opposing forces has important implications for novel theorizing on the use of Agile in the front end of digital innovation, transfer practices from Research to Development in a hybrid setting, as well as for theorizing about digital innovation management.

CO2 regulations on heavy-duty transport are introduced in essentially all markets within the next decade, in most cases in several phases of increasing stringency. To cope with these mandates, developers of engines and related equipment are aiming to break new ground in the fields of combustion, fuel and hardware technologies. In this work, a novel diesel fuel injector, Delphi’s DFI7, is utilized to experimentally investigate and compare the performance of ramped injection rates versus traditional square fueling profiles. The aim is specifically to shift the efficiency and NOx tradeoff to a more favorable position. The design of experiments methodology is used in the tests, along with statistical techniques to analyze the data. Results show that ramped and square rates - after optimization of fueling parameters - produce comparable gross indicated efficiencies. Tests were carried out at 1200 and 1425 rpm; for the latter engine speed peak efficiency was attained at considerably lower NOx levels by applying a ramped injection rate. Particulate matter emissions, on the other hand, are generally lower with the use of square profiles. Heat release analysis further reveals that ignition delays in ramped rate operation are quite long, hinting at vastly different spray behavior. The relatively low loads applied in this work only sustain the delays further. Altogether, this causes the potential of the rate shaping capabilities to be underexploited, as direct control over the burn rate is limited with the combustion system used in this work. The results emphasize the need to carefully select ramp slopes for a particular engine geometry, load and speed point, and additional operating parameter settings.